For many audio applications, a process is required to obtain an accurate estimate of the fundamental and harmonics of periodic sections of the audio signal. More generally, any digital version of a periodic signal can potentially have an associated fundamental frequency component, along with harmonics which are frequency components located at integer multiples of the fundamental. In this description, the focus will be on audio applications and speech applications in particular, without loss of generality to applications outside the speech and audio domains.
For speech, tracking and assessment of fundamental and harmonic frequencies can be a key step in accomplishing such tasks as automated speaker identification, speech data compression, pitch alteration and natural sounding time compressions and expansions [1]. Linguists and speech therapists also use such tracking and assessment for prosodic analyses and training [2].
Various methods of fundamental and harmonic frequency tracking have been proposed and developed, but most have been based on other low resolution techniques such as FFT and cepstral analyses [1]. This is as opposed to using super-resolution frequency estimation as provided by the Matrix Pencil (MP) technique [3]. The prior art in the area of super-resolution speech fundamental determination consists of the “super resolution pitch determinator” (SRPD) [4] and the “enhanced super resolution pitch determinator” (eSRPD) [5] methods. Because these prior methods do not explicitly process a spectral representation or decomposition of the input audio signal, they are not considered to be in the same class as the present invention. However, the SRPD and the eSRPD do provide a baseline for comparisons when assessing the performance of the subject invention and will therefore be referred to in the context of performance.